The Role Of Individual Capital In Learning And Knowledge Sharing

The Role Of Individual Capital In Learning

And Knowledge Sharing

Empirical Results From The U.S. Hospitality Industry

University of Groningen

Faculty of Economics and Business

MSc. International Business and Management

August 2013

A

BSTRACT

This study aims to shed light on the role of individual capital in MNCs’ ability to engage in knowledge transfer on intra-organizational level. Bourdieu’s theory of practice is adopted as the theoretical basis. The notion of economic, cultural, social and symbolic capital are presented in order to develop an understanding of the factors affecting individual learning and knowledge sharing behavior. The empirical results from the questionnaire show that employees holding a great volume of cultural, social and symbolic capital are more likely to engage in learning and knowledge sharing. There is no significant association between economic capital and attitudes to learning and knowledge sharing. Therefore, effective knowledge management should take into account the composition of capital that individuals draw on in order to pursue their choices with regard to learning and knowledge sharing within MNCs.

Keywords: Knowledge transfer, Learning, Knowledge sharing, Capital, Bourdieu, Hospitality

T

ABLE OF CONTENTS

INTRODUCTION ... 5

1. LITERATURE REVIEW ... 8

1.1 KNOWLEDGE THEORIES ... 8

1.1.1 The concept of knowledge ... 8

1.1.2 The importance of knowledge to MNCs ... 9

1.1.3 Learning and knowledge sharing ... 10

1.1.4 Types of knowledge ... 12

1.1.5 The process of knowledge transfer ... 16

1.1.6 Knowledge transfer mechanisms ... 21

1.1.7 Facilitators and impediments to knowledge transfer ... 23

1.2 INDIVIDUAL LEARNING AND KNOWLEDGE SHARING BEHAVIOR ... 25

1.2.1 Bourdieu’s theory of practice ... 26

1.2.2 Attitudinal consequences of capital ... 28

2. CONCEPTUAL MODEL ... 32

2.1 INDIVIDUAL CAPITAL AND ATTITUDES TO LEARNING AND KNOWLEDGE SHARING ... 33

2.1.1 Economic capital and attitudes to learning and knowledge sharing ... 33

2.1.2 Cultural capital and attitudes to learning and knowledge sharing... 34

2.1.3 Social capital and attitudes to learning and knowledge sharing ... 35

2.1.4 Symbolic capital and attitudes to learning and knowledge sharing ... 35

2.2 THE MODERATING ROLE OF KNOWLEDGE TRANSFER PRACTICES ... 36

2.3 PERFORMANCE AND ATTITUDES TO LEARNING AND KNOWLEDGE SHARING ... 37

3. RESEARCH DESIGN ... 38

3.1 RESEARCH STRATEGY ... 38

3.2 CASE STUDY ... 38

3.4 SAMPLE SIZE ... 45

4. RESULTS ... 47

4.1 SAMPLE CHARACTERISTICS ... 47

4.2 ANALYSIS OF THE MODEL’S CONSTRUCTS ... 47

4.2.1 Individual capital ... 48

4.2.2 Attitudes to learning and knowledge sharing ... 54

4.2.3 Knowledge transfer practices ... 55

4.2.4 Performance ... 62 4.3 HYPOTHESES TESTING ... 62 4.3.1 Correlations ... 62 4.3.2 Regression analysis ... 66 4.3.3 Conclusion ... 74 5. DISCUSSION ... 76 6. CONCLUSION ... 81

6.1 LIMITATIONS AND CONTRIBUTIONS ... 83

6.2 FUTURE RESEARCH ... 83

ACKNOWLEDGEMENT ... 85

7. REFERENCES ... 86

8. APPENDIXES ... 95

8.1 APPENDIX A – Questionnaire ... 95

8.2 APPENDIX B – Overall experience scores ... 102

8.3 APPENDIX C – Regression model – Attitudes to learning ... 102

8.4 APPENDIX D – Regression model – Attitudes to knowledge sharing ... 103

LIST OF FIGURES

Figure 1–1: Knowledge management value chain………. 16

Figure 1–2: Nine knowledge transfers………... 18

Figure 1–3: Knowledge spiral model………. 20

Figure 1–4: The space of social positions and lifestyles……….... 29

Figure 2–1: Conceptual model………... 32

LIST OF TABLES Table 1–1: Features of explicit and tacit knowledge………. 15

Table 1–2: Information richness of knowledge transfer mechanisms………... 22

Table 1–3: Relationship between knowledge characteristics and knowledge transfer mechanisms……….. 23

Table 3–1: Construct and variables……….... 45

Table 4–1: Annual personal income………... 48

Table 4–2: Education………. 49

Table 4–3: Education parents………. 49

Table 4–4: Role model………... 50

Table 4–5: Representation of cultures………... 51

Table 4–6: Reliability of construct – Social capital………... 52

Table 4–7: Validity and reliability of construct – Nomination……….. 53

Table 4–8: Reliability of construct – Attitudes to learning and knowledge sharing……. 55

Table 4–9: Use of knowledge management tools……….. 56

Table 4–10: Composition of knowledge conversion processes………. 57

Table 4–11: Use of knowledge conversion processes………... 58

Table 4–12: Reliability of construct – Knowledge transfer practices………... 59

Table 4–13: Content of knowledge sharing………... 60

Table 4–14: Factor analysis - Content of knowledge sharing………... 61

Table 4–15: Guest versus strategic knowledge sharing across the divisions………. 62

Table 4–16: Measures of association………. 63

Table 4–17: Correlation matrix……….. 64

Table 4–18: Summary of results……… 75

Table 8–1: Overall experience scores……… 102

Table 8–2: Regression model – Attitudes to learning………... 102

Table 8–3: Regression model – Attitudes to knowledge sharing……….. 103

Table 8–4: Regression model – The moderating role of knowledge transfer practices.... 104

I

NTRODUCTION

The increasing importance of knowledge has attracted researchers to analyze organizations in terms of their function to process knowledge. The ability to transfer knowledge is recognized as a key determinant of the organization’s capacity to build and maintain sustainable competitive advantage within organizations and between them (Szulanski, 1996). Multinational corporations (MNCs) need to transfer and acquire new knowledge as they seek to develop new products and survive (Henderson and Cockburn, 1994). As evidenced by organizations’ increased use of strategic alliances, and mergers and acquisitions to acquire knowledge, transferring knowledge from external sources has become important to organizations’ success (Lane, Salk and Lyles, 2001). Evidence is also accumulating that intra-organizational knowledge transfer provides competitive benefits (e.g. Gupta and Govindarajan, 2000; Schulz, 2001). Research has shown that both inter- and intra-organizational knowledge transfers have important implications for intra-organizational performance and innovativeness (Day, 1994; Tsai, 2001). Szulanski (1996) argues that organizational knowledge transfer contributes to the development of organizational capabilities that are difficult to imitate, and subsequently leads to higher levels of performance. Besides, transfer of knowledge stimulates the combination of existing and newly acquired knowledge and enhances an organization’s capacity to generate new ideas for product development (Jansen, Van den Bosch and Volberda, 2005).

defines capital as ‘’accumulated labor in its materialized form or its ‘’incorporated’’, embodied form that individuals draw on and deploy in order to pursue their life choices’’. Individual capital can present itself in four fundamental forms: (1) economic capital, (2) cultural capital, (3) social capital, (4) symbolic capital. Individual capital can play a central role in explaining MNCs’ ability to engage in knowledge transfer. Besides, an understanding of the role of individual capital may influence decisions regarding the allocation of resources and guide MNCs in their knowledge management efforts (Chong, Chong and Lin, 2010).

This study examines the transfer of knowledge by understanding how MNCs implement learning and knowledge sharing in practice. The transfer of knowledge requires not just the willingness of those employees who possess knowledge to share and communicate it but also the willingness of the acquirer to absorb knowledge (Robertson and O’Malley Hammersley, 2000). Individuals differ from one another in their willingness to learn from others and share knowledge. The purpose of this study is to identify the role of individual capital in differences in attitudes towards learning and knowledge sharing within MNCs. This leads to the following research question;

To what extent can individual capital explain differences in attitudes towards learning and knowledge sharing within MNCs?

This study adds to the body of knowledge management literature by deepening the understanding of the factors affecting individuals’ learning and knowledge sharing behavior in the organizational context. For researchers the study might give some new insides in the role that individual capital plays in the intra-organizational knowledge transfer process. For managers this study might be of interest since it offers new insides in factors that influence employees’ attitudes towards learning and knowledge sharing. An understanding of the impact of individual capital may influence management decision making regarding the allocation of resources and could guide management in their knowledge management efforts. MNCs could make more efficient strategic decisions by understanding the relative influence of individual capital. This is important since the transfer of knowledge is a costly strategy for MNCs.

1.

L

ITERATURE REVIEW

This chapter surveys the existing literature to obtain better insight in the field of knowledge management and contains two different sections. In the first section theoretical considerations about knowledge, knowledge management and the knowledge transfer process are discussed. Subsequently, the fundamental concepts proposed by Bourdieu’s theory of practice (1986), including different forms of capital, habitus and the field, are reviewed in order to develop an understanding of the factors influencing individual learning and knowledge sharing behavior within MNCs.

1.1 KNOWLEDGE THEORIES

In this section the concept of knowledge, its main features, its relevance to MNCs and the knowledge transfer process are examined to define and describe the foundation and dimensions of knowledge management.

1.1.1 The concept of knowledge

In order to obtain better insight in the field of knowledge management, first the concept of knowledge needs to be defined. Several definitions of knowledge from reputable authors are referred to; according to Van der Spek and Spijkervet (1997: 13) ‘’knowledge is the whole set of insights, experiences and procedures which are considered correct and true, and which therefore guide the thoughts, behaviors, and communications of people’’. Davenport and Prusak (1998: 5) define knowledge as ‘’a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms’’. The given definition by Davenport and Prusak (1998) is used in this study since it gives the most accurate explanation of what knowledge entails in relation to this research.

interchangeable concepts. Davenport and Prusak (1998: 2) define data as ‘’a set of discrete, objective facts about a subject or event. In an organizational context, data is most usefully described as structured records of transactions’’. Data is essential to organizations since it is important raw material for the creation of information. There is no inherent meaning in data, it consists of signs and labels only a fragment of what occurred; data does not give an interpretation, judgment or basis of action (Davenport and Prusak, 1998). According to Bolisani and Scarso (1999) information, representing the fundamental basis for the evolvement of knowledge, is derived from data. Data becomes information when its creator adds meaning (i.e. data with significance). However, information needs to be interpreted, and understanding what information may mean requires knowledge (Bolisani and Scarso, 1999). Hence, knowledge could be seen as the capacity, embodied in the brain of individuals and embedded in social practices, to interpret information and to transform information in new knowledge (Davenport and Prusak, 1998). While data can be found in records or transactions and information in messages, knowledge can be obtained from an individual or groups of people and is embedded in organizational processes and routines. Therefore, a major difference between these concepts is that data and information can be independent of people, while knowledge belongs to the individual. In other words, knowledge is not only context-specific and relational, but also related to values, beliefs and actions of individuals (Nonaka and Takeuchi, 1995).

1.1.2 The importance of knowledge to MNCs

When dealing with the aspect of competitive advantages, two theories have emerged: the resource-based view and the knowledge-based view of the organization. The resource-based view perceives the organization as a unique bundle of idiosyncratic resources and capabilities which are difficult to copy by other organizations (Grant, 1996). Grant (1996) argues that organizations need to maximize value through the optimal exploitation of resources and capabilities, while developing the organization's resource base for the future. The knowledge-based view of the organization is an extension of the resource-knowledge-based theory. Under this perspective knowledge is considered to be the major resource of an organization in terms of its contribution to the value added and strategic significance (Grant, 1997). The focus on resources and capabilities that are created within the organization and not easy to copy or adopt by competitors puts organizational knowledge in a prominent position as the major source of competitive advantage (Teece, Pisano and Shuen, 1997). Nonaka and Takeuchi (1995) argue that the capability of an organization to create new knowledge, communicate it throughout the organization and incorporate it in products, systems and services may be a preeminent success factor. Similarly, Argote and Ingram (2000) state that the creation and transfer of knowledge in organizations provide a basis for sustainable competitive advantage, which ultimately can lead to improved organizational performance. Hence, the knowledge base of an organization is considered as an important asset since it has great potential to enhance performance (Tsai, 2001). Knowledge and employee expertise can be seen as important sources of value creation. Therefore, an important challenge for MNCs is to improve the processes by which knowledge is generated, disseminated, integrated and coordinated (Jordan and Jones, 1997). Learning to manage knowledge and employee expertise holds great potential for improved organizational performance (Lank, 1997).

1.1.3 Learning and knowledge sharing

organizational slack implies that much knowledge which resides in the MNC has not been fully applied to organizational advancement. Most MNCs do not make use of more than half of the knowledge available to the organization (Chini, 2004). The orphaned knowledge can be captured and transformed and the overlapping knowledge can be refined and enriched through knowledge sharing practices and individual learning within the organization. Therefore, it is not sufficient for a MNC to only own knowledge; it needs to transfer the knowledge throughout the organization as well. Organizational knowledge sharing is concerned with exchanging knowledge from one unit of the organization to another, whereby a sender and a receiver are involved (Szulanski, 1996). Bartol and Srivastava (2002: 65) define organizational knowledge sharing as ‘’the interaction in which employees diffuse relevant information to others across the organization’’. Learning and knowledge sharing can be viewed as two sides of the same coin, every knowledge sharing occasion can be seen and used as a learning opportunity, and both are necessary for effective knowledge transfer in organizations. The major goal of sharing employees’ knowledge is its transfer to organizational resources and assets (Dawson, 2001). The transfer of knowledge is constituted according to three process steps: (1) Disembedding; detaching knowledge from the source unit in order to be transferable, (2) Transfer; moving knowledge across time and space from the source unit to the receiving unit, (3) Re-embedding or integration; translation and integration of the transferred knowledge into the receiving unit (Czarniawska and Joerges, 1996). The transfer is effective if the knowledge can be embedded into (new) organizational practices.

of learning can be distinguished within the organizational learning process. The first form of learning is called first-order learning, which consists of ‘’a routine, incremental, conservative process that serves to maintain stable relations and sustain existing rules’’ (Lant and Mezias, 1992: 48–49). It is basically the process to further exploit an organization’s existing activities, routines and technologies in a way that does not change underlying values or assumptions (Arthur and Aiman-Smith, 2001). Hence, first-order learning identifies the possibility to correct errors by making small adjustments so current practices can function more efficiently, however, without correcting the underlying policies. The second form of learning is labeled second-order learning and has been described behaviorally by Lant and Mezias (1992: 49) as ‘’the search for and exploration of alternative routines, rules, technologies, goals and purposes, rather than merely learning how to perform current routines more efficiently’’. Second-order learning refers to more fundamental changes in organizational goals and norms and enables organizations to change existing patterns of behaviors and thoughts by exploring different ways of thinking and doing things (Arthur and Aiman-Smith, 2001). When organizations realize that certain experiences cannot be interpreted within the current organizational paradigm second-order learning will be encouraged (Lant and Mezias, 1992). Finally, third-order learning is concerned with intensively questioning of both the context and meaning surrounding the learning, it extends second-order leaning by asking questions as to the purpose of the learning or the principles upon which it is based (Yuthas, Dillard and Rogers, 2004). Accordingly, third-order learning is about questioning how one learns and then reflecting critically upon the questioning process itself. It is a continual reflection on the learning process which has been reduced to its simplest form by various scholars and researchers as ‘’learning to learn how to learn’’ (Yuthas et al., 2004: 238). Organizational learning facilitates MNCs to create new knowledge and improve procedures and strategies through continuous collective learning processes (Yang, 2008).

1.1.4 Types of knowledge

indicate that knowledge characteristics differ according to their degree of tacitness. A distinction can be made between ‘’explicit or articulated’’ and ‘’tacit or implicit’’ knowledge. The philosopher Michael Polanyi (1966) first introduced the concept of explicit versus tacit knowledge. Today, this explicit-tacit dichotomy represents in the literature on organizational knowledge one of the most widely recognized distinctions between different types of knowledge.

Explicit knowledge

Explicit knowledge refers to knowledge that consists of some systematic language and is codified through numbers, codes or words (Hedlund, 1994). Nonaka and Teece (2001) note that explicit knowledge can be shared in well-structured forms of written mediums or data, such as reports, manuals and scientific formulas. It can be captured in text, tables or diagrams and this codification makes it amenable to transfer (Riesenberger, 1998). Due to these characteristics, explicit knowledge is easily communicable and easy to store. There is little chance of losing explicit knowledge due to employee turnover since this type of knowledge is articulated, codified and available in organizational records, such as archives and databases (Jasimuddin, Klein and Connell, 2005). Explicit knowledge can be accessed and used easily via information and communication technology (ICT) by anyone in the MNC, which infers that it can be transferred around the world quickly. The study of Kogut and Zander (1995) shows that the degree of codification has a significant influence on the speed of knowledge transfer, at which knowledge characterized by a high degree of codification is faster and easier transferrable. Therefore, knowledge with a great extent of explicitness can be transferred more rapidly, making it easily available to large numbers of people. However, knowledge which can be easily transferred within the organization is more likely to be imitated by competitors (Kogut and Zander, 1995). Hence, by using explicit knowledge MNCs face a high risk of imitation by competitors, leading to loss of competitive advantage (Jasimuddin et al., 2005).

Tacit knowledge

explicitly is only a minor part; he addresses that ‘’we can know more than we can tell’’. Due to its implicit nature, tacit knowledge is more difficult to access, formalize and transfer than explicit knowledge (Jasimuddin et al., 2005). On the organizational level, tacit knowledge is embedded in organizational procedures, routines, systems, values and beliefs (Nonaka and Teece, 2001; Lucas, 2006). Other organizations find it difficult to understand and imitate tacit knowledge. Therefore, tacit knowledge held by the MNC is the most strategically significant type of knowledge and creates the basis for a sustainable competitive advantage (Chini, 2004). Though, there are some difficulties concerned with tacit knowledge. An organization cannot store tacit knowledge outside the human mind without some process of articulation. This type of knowledge is context specific and cannot be captured and converted easily (Davenport and Prusak, 1998). Extensive personal contact and trust is required in order to share tacit knowledge effectively (Nonaka, 1994).Tacit knowledge remains personal unless it is articulated through social interaction, such as personal training, mutual meetings or practical experience. Mutual trust is a crucial base for facilitating this type of constructive collaboration (Nonaka, 1994). The most distinctive problem MNCs face regarding tacit knowledge is the risk of losing this type of knowledge; as employees hold knowledge without sharing it and depart for other organizations, the knowledge will be invisible transformed into knowledge lost (Yang, 2004).

TABLE 1–1

Features of explicit and tacit knowledge

Features Explicit knowledge (i.e.

documents, codes and tools)

Tacit knowledge (i.e. skills and experience of employees)

Content Codified Non-codified

Articulation Easy Difficult

Location Computers, artefacts Human brains

Communication Easy Difficult

Media Information technology and

other archives Face-to-face contact, storytelling

Storage Easy Difficult

Strategy Impersonalization Personalization

Ownership Organization Organization and its members

(source: Jasimuddin, Klein and Connell, 2005)

In this study, explicit and tacit knowledge are distinguished from one another. However, some researchers argue that explicit and tacit knowledge should not be seen as two separate types of knowledge (e.g. Inkpen and Dinur, 1998; Hall and Andriani, 2003). Instead, Inkpen and Dinur (1998: 456) argue that ‘’the distinction between explicit and tacit knowledge should not be viewed as a dichotomy but rather as a spectrum with the two knowledge types at either end’’. The spectrum of knowledge runs from explicit knowledge at one extreme to tacit knowledge at the other (Hall and Andriani, 2003).

The most prominent model building on the dichotomy of explicit and tacit knowledge is that of Nonaka and Takeuchi (1995). In their pioneering work Nonaka and Takeuchi propose a model of knowledge creation within organizations. They argue that organizational knowledge can be created through interactions between explicit and tacit knowledge; the individual is the prime mover in the process of organizational knowledge creation (Nonaka and Takeuchi, 1995). In the next paragraph their work will be further discussed.

(Thorbjornsen and Mouritsen, 2003). Individual knowledge constitutes the basis for the development of organizational knowledge, for instance, a production process is developed from what was once the knowledge of individuals, hence this embedded knowledge became independent of the individuals who created the production process and therefore has some organizational stability (Davenport and Prusak, 1998). Organizational knowledge is embedded knowledge and consists of collective memories, references, norms, values and belief systems (Chini, 2004). Kriwet (1997) notes that organizational knowledge is more than the sum of individual knowledge bases, since it resides in the relations between individuals and within groups of people. Individuals need to keep modifying their knowledge through interactions with other employees in order to achieve complete organizational knowledge (Liebowitz, 1999). This type of knowledge is captured by the MNC’s systems, products, processes, policies, rules, history and culture (Beckman, 1999).

1.1.5 The process of knowledge transfer

Within this study knowledge management is conceptualized as a process. The process of managing the different types of knowledge is divided into four phases in the knowledge management value chain (Shin, Holden and Schmidt, 2001). The knowledge management value chain distinguishes between the creation, storage, distribution and application of knowledge (Figure 1–1). However, researchers have presented different links to build the knowledge management value chain.

FIGURE 1–1

Knowledge management value chain

The first phase of the knowledge management value chain is the creation of knowledge. The requisite for knowledge management is the recognition that unique knowledge exists in an internal or external source, such as an organizational unit or a customer (Chini, 2004). The creation of knowledge is related to knowledge addition and the correction of existing knowledge by finding more sources of knowledge and extending the knowledge network (Shin et al., 2001). The second phase is concerned with the storage of knowledge and relates to the maintenance of knowledge in individual and organizational memory. This phase has to be adjusted according to the type of knowledge and receiver characteristics. Next to the existence of an individual or organizational memory device, the willingness of employees to share the individual knowledge is vital in order to permit storage (Chini, 2004). The third phase, knowledge distribution, includes the dyadic exchange of knowledge between a source and recipient unit. The strategy applied to manage the transfer process depends on the type of knowledge (Davenport and Prusak, 1998). However, during the transfer process problems often emerge; the notion of internal stickiness implies the difficulty of transferring knowledge within MNCs (Szulanski, 1996). Szulanski (1996) argues that four sets of factors influence the difficulty of transferring knowledge: (1) characteristics of the knowledge transferred, (2) characteristics of the source of knowledge, (3) characteristics of the recipient of knowledge, (4) characteristics of the context in which the transfer takes place. The results of Szulanski’s (1996) study suggest that knowledge-related barriers are most important origins of internal stickiness, e.g. the recipient’s lack of absorptive capacity and causal ambiguity. The final phase, knowledge application, seeks to locate the source of competitive advantage (Shin et al., 2001). A major challenge is the integration of internal knowledge and the knowledge acquired from outside in order to increase value, since the transfer of knowledge is successful only if the newly absorbed knowledge leads to the creation of new ideas or changes in behavior (Davenport and Prusak, 1998). Overall, the knowledge management value chain should be strategically driven in order to realize the objectives of the MNC (Shin et al., 2001). To deliver value, each knowledge management system has to be linked to the organization’s vision, corporate strategy, structure and processes (Chini, 2004).

knowledge outside the MNC, such as other organizations and customers (Chini, 2004). This study focuses on intra-organizational knowledge transfers. Sveiby (2001) distinguishes nine different knowledge transfers, which have the potential to create value for a MNC (Figure 1– 2).

FIGURE 1–2

Nine knowledge transfers

(source: Sveiby, 2001)

All knowledge transfers involving external sources or recipients are excluded from this study. Besides, the transfer process ‘’within internal structure’’ clarifies only the management of knowledge within the storage system and exceeds the focus of this research. Therefore, three of these knowledge transfers are relevant for this study:

 Knowledge transfers between individuals: This knowledge transfer takes place in communication between employees and is concerned with how the transfer of knowledge between people in the MNC and the collaborative climate can be improved (Sveiby, 2001). The most important issues are trust and exposure to different kinds of expertise in the organization (Chini, 2004).

repositories can be improved (Sveiby, 2001). When knowledge of individual competences is stored in repositories, such as systems, tools and templates, it can be shared more easily with the whole organization (Chini, 2004). Issues such as the climate in the MNC and the level of involvement from all employees in the system are important in order to create value from data repositories (Sveiby, 2001).

 Knowledge transfer from internal structure to individual competence: This knowledge transfer is concerned with how individuals’ competence can be improved by using systems, tools and templates (Sveiby, 2001). Knowledge in the internal system should be made available to employees in such a way that they improve their capacity to act (Sveiby, 2001). An important issue is the interface between employees and knowledge storage systems (Chini, 2004).

By means of Sveiby’s (2001) model of the nine knowledge transfers, the complexity of organizational knowledge transfer could be visualized. In order to understand the complexity of knowledge transfer processes, three crucial periods or elements occurring during the transfer of knowledge can be distinguished: (1) locution, (2) illocution, (3) perlocution (Austin, 1962). Locution implies the utterance of language. If language is used in making an utterance, this movement is called illocution by Austin (1962) and indicates the dialogical phase where the knowledge transfer takes place. The response of the receiver is called perlocution. A discrepancy between what is meant by a sender and inferred by a receiver might lead to ineffective knowledge transfer, and MNCs face a risk of knowledge loss in the knowledge transfer process. Two general approaches to knowledge transfer processes can be distinguished: (1) the communication model (Shannon, 1948), (2) the knowledge spiral model (Nonaka and Takeuchi, 1995).

The communication model

message is noise. This model is widely applied in the field of knowledge management. Szulanski (1996) was one of the first to introduce the concept of the communication model into the knowledge management literature. Szulanski (1996) conceptualized knowledge transfer as a message transmission through a channel from a sender to a receiver in a given context.

The knowledge spiral model

Nonaka and Takeuchi’s (1995) model of organizational knowledge creation is referred to as ‘’knowledge spiral model’’ and builds on the dichotomy of explicit and tacit knowledge (Figure 1–3).

FIGURE 1–3 Knowledge spiral model

(source: Nonaka and Takeuchi, 1995)

The main idea of the model is that explicit and tacit knowledge are constantly interacting with each other; this interaction is called knowledge conversion (Nonaka, 1994). Nonaka and Takeuchi (1995: 72) emphasize that ‘’knowledge creation is a spiraling process of interaction between explicit and tacit knowledge’’. Hence, the knowledge spiral model does not only explain the creation of knowledge but also describes processes of transferring knowledge; indicated as the conversion processes (Chini, 2004). Four modes of knowledge conversion can be distinguished; the fundamental purpose of these four modes is the creation and expansion of organizational knowledge through conversion between explicit and tacit knowledge:

during the transfer phase, such as shared technical skills and mental models (Bolisani and Scarso, 1999). Experience is the key to acquiring tacit knowledge (Nonaka, 1994).  Externalization (from tacit to explicit knowledge): In this process tacit knowledge is converted into explicit knowledge by codifying it in the form of explicit concepts, formal models, metaphors etc. (Nonaka and Takeuchi, 1995). Through this transformation tacit knowledge becomes collective group knowledge and can be made available on a organization-wide basis. The externalization process is normally seen as very difficult.

 Combination (from explicit to explicit knowledge): In the process of combination existing elements of explicit knowledge are combined (e.g. through sorting or recategorizing) in order to create new explicit knowledge (Nonaka and Takeuchi, 1995). Through combination, explicit knowledge is transformed into systematic sets of knowledge within a knowledge system. ICT supports the combination process since explicit knowledge becomes accessible and is able to reach its intended target(s).  Internalization (from explicit to tacit knowledge): In this process explicit knowledge

becomes organization-wide shared knowledge and is absorbed and converted into specific ‘’know-how’’ by its members, becoming integrated into their individual knowledge base (Nonaka, 1994). Employees continuously engage in ‘’learning by doing’’ by reading or practicing, e.g. through manuals or training programmes. Hence, the knowledge becomes a valuable asset for the MNC.

The core principle of the knowledge spiral model is that tacit knowledge has to be mobilized and converted (Chini, 2004), thereby making it explicit and transferable and so collectively available in order to become eventually an organization-wide knowledge asset.

By combining the communication model and the knowledge spiral model, the four modes of knowledge conversion can also be viewed as single transfers between a source and a recipient (Chini, 2004). Therefore, in order to manage the knowledge flows within the MNC every sourcing and receiving unit has to engage in some of these knowledge conversion processes.

1.1.6 Knowledge transfer mechanisms

add to value creation (Hutzschenreuter and Horstkotte, 2010). The choice which transfer mechanism has to be used depends on the type of knowledge a MNC wants to transfer. As Hansen, Nohria and Tierney (1999) argue that the right degree of knowledge codification and personalization should be found, next to the right choice of knowledge transfer mechanism. Therefore, it is essential that MNCs use the transfer mechanism that suits the specific knowledge characteristics. Pedersen, Petersen and Sharma (2003) classify mechanisms of knowledge transfer in a simplified way: (1) rich communication media, (2) written media. The degree of information richness of knowledge transfer mechanisms is illustrated in Table 1–2, at which the two transfer mechanisms identified by Pedersen et al. (2003) constitute the two extremes.

TABLE 1–2

Information richness of knowledge transfer mechanisms Information

richness Medium

High 1. Face-to-face interaction (training, meetings, visits) 2. Video conferencing 3. Telephone

4. Electronic

(e-mail, intranet, internet) 5. Written, personal (letters, memos) 6. Written, formal (documents, manuals) Low 7. Numeric, formal

(computer output)

(note: Adapted from Daft and Lengel, 1984; Vickery, Droge, Stank, Goldsby and Markland, 2004)

process and transfer the knowledge (Windsperger and Gorovaia, 2011). This notion is also supported by Pedersen et al. (2003); they find evidence that organizations mainly transfer tacit knowledge through rich communication media and explicit knowledge through written media. Therefore, the more tacit (explicit) the knowledge is, the more knowledge transfer mechanisms with a higher (lower) degree of information richness are needed to enable an efficient knowledge transfer (Windsperger and Gorovaia, 2011). By using unsuitable knowledge transfer mechanisms MNCs face a risk of knowledge loss in the knowledge transfer process or unnecessarily high communication costs (Pedersen et al., 2003). For instance, if the knowledge is codifiable it is not efficiently transferred by using high information rich knowledge transfer mechanisms. Although high information rich mechanisms enable the transfer of codifiable knowledge, it is not efficient since the transfer of knowledge through high information rich mechanisms is costly due to e.g. high set-up costs. Table 1–3 depicts the relationship between knowledge characteristics and knowledge transfer mechanisms.

TABLE 1–3

Relationship between knowledge characteristics and knowledge transfer mechanisms

Type of knowledge Explicit Tacit

Knowledge transfer mechanism

High information rich MISFIT

(High communication costs) FIT

Low information rich FIT MISFIT

(Knowledge loss)

(note: Adapted from Windsperger and Gorovaia, 2011)

To optimize knowledge flows within MNCs, efficient coordination has to ensure that employees share knowledge through appropriate transfer mechanisms (Chini, 2004). The knowledge management infrastructure of MNCs has to be well developed in order to maximize the exploitation of knowledge that is embedded within the organization and its employees (Chini, 2004).

1.1.7 Facilitators and impediments to knowledge transfer

knowledge. In order to learn something new, an employee must already have enough related knowledge to absorb the new knowledge, this becomes evident in the recipient unit’s ability to value, assimilate and apply new knowledge successfully (Szulanski, 1996). Consequently, this leads to misunderstanding between people during the transfer process and may result in the termination of learning from each other. Therefore, MNCs should encourage knowledge sharing activities and promote feedback.

1.2 INDIVIDUAL LEARNING AND KNOWLEDGE SHARING BEHAVIOR

While much of the early knowledge management literature was mainly focused on technological matters, this has changed, such that the importance of people has been more recognized (e.g. Szulanski, 1996; Davenport and Prusak, 1998). Technology clearly plays a crucial role in approaches to managing knowledge. However, as Davenport and Prusak (1998) argue, the technology is designed and operated by people and its contribution to managing knowledge depends on fitting the social context of an organization. The knowledge management literature has reached the point of acknowledging that the success of knowledge management initiatives is fundamentally predicated on people. While the importance of people in the field of knowledge management has been widely discussed, there exists a general lack of depth to the contemporary understanding of how human and social factors affect knowledge management initiatives.

shapes the willingness (or reluctance) of employees to learn new knowledge and skills and share their knowledge and expertise. The next paragraphs shed light on this question by presenting Bourdieu’s theory of practice, which contains fundamental concepts for this study. Bourdieu’s theory of practice is adopted as the theoretical basis to develop an understanding of the factors influencing individual learning and knowledge sharing behavior within MNCs.

1.2.1 Bourdieu’s theory of practice

The fundamental concepts proposed by Bourdieu’s theory of practice include: capital, habitus and field. Bourdieu (1977) states that different forms of capital, habitus and the field all work together to generate practice. The ideas of Bourdieu have not been extensively drawn upon in the organization and management literature (Özbilgin and Tatli, 2005). One reason for this absence is the fact that Bourdieu’s work is relatively difficult to comprehend. According to Everett (2002: 77) is this problem a function of the following three aspects: ‘’(1) the sheer size of Bourdieu’s work (over two dozen books and two hundred articles), (2) the fact that Bourdieu’s work is written in French, (3) the difficult writing style’’. However, as Everett (2002) suggests, Bourdieu’s work has much to offer organization and management studies. The utilization of Bourdieuan concepts may advance theory building in the field of knowledge management. Next, the concept of capital, habitus and field are described in detail.

subsequent sections institutionalized cultural capital is referred to as cultural capital. Social capital consists of social obligations (i.e. ‘’connections’’) and is under certain conditions convertible into economic capital (Bourdieu, 1986). This capital manifests as the resources and powers derived from networks of relationships; the added value of being a member of a group. Bourdieu (1986: 255) defines symbolic capital as ‘’capital in whatever form, insofar as it is represented, i.e. apprehended symbolically, in a relationship of knowledge or more precisely of misrecognition and recognition’’. Symbolic capital arises out of the other forms of capital as economic, cultural and social capital are converted to symbolic capital the moment they are deemed legitimate as basis for claiming prestige, respect and / or authority within a given field (Everett, 2002). Each form of capital is manifested in a different ‘’currency’’ (e.g. money, physical objects or qualifications). Economic capital is at the root of all the other forms of capital since in principle the different forms of capital can be derived from economic capital. Most of the properties of cultural, social and symbolic capital can be deduced from the fact that, in the fundamental state, they are linked to the body and presuppose embodiment (Bourdieu, 1986). Cultural, social and symbolic capital present the immaterial forms of capital. The accumulation of immaterial forms of capital presuppose a process of embodiment which costs time, time which must be invested personally by the individual (Bourdieu, 1986). The work of acquisition of immaterial forms of capital is work on oneself (i.e. self-improvement), an effort that presupposes a personal cost (Bourdieu, 1989). According to Bourdieu (1986) the immaterial capital is external wealth converted into an integral part of the person, into a habitus. ‘’The habitus is embodied history, internalized as a second nature and so forgotten as history which functions every moment as a matrix of perceptions, appreciations and actions’’ argues Bourdieu, ‘’the active presence of the whole past of which it is the product’’ (Bourdieu, 1990: 56). This ‘’personal’’ capital cannot be transmitted instantaneously, unlike money or property rights, by gift, purchase or exchange.

Field refers to the system or structure in which people function in pursuit of desirable resources. Fields are historical constellations that are not static but arise, grow, change shape and sometimes perish over time (Wacquant, 2006). Bourdieu and Wacquant (1992)argue that individuals exist as agents who are functioning in the field under consideration by the fact that they have the required properties to be effective and to produce effects in this field. For instance, education, religion, politics and business are all fields which function in a different way. As suggested by Lounsbury and Ventresca (2003), the MNC can be conceptualized as a field which provides a systematic approach for organizational research to explore structure and agents in a single framework.

There exists an interdependency among these three concepts (i.e. capital, habitus and field). Dynamics pertaining to different forms of capital are determined by habitus and the field; capital does not have an independent existence of habitus and the field. On the other hand, habitus and the field owe their existence to the actions of individuals since these actions reproduce and transform habitus and the field (Özbilgin and Tatli, 2005). Özbilgin and Tatli (2005: 864) argue ‘’that individuals use strategies to transform, allocate and distribute their volume of capital among different forms, which, in turn, determine the boundaries of their agency (i.e. the sphere of individuals active action) within the habitus and field they are acting in’’.

The notion of capital, habitus and the field are presented in order to explain differences in attitudes towards learning and knowledge sharing within MNCs. Effective knowledge management has to take into consideration the underlying characteristics of the organization’s knowledge base (Li et al., 2010). However, little is known about the role of economic, cultural, social and symbolic capital in an organization’s ability to engage in knowledge transfer on intra-organizational level. The composition of economic, cultural, social and symbolic capital that employees detain will be related to employees attitudes to learning and knowledge sharing in order to explain differences in attitudes towards learning and knowledge sharing within the organizational field.

1.2.2 Attitudinal consequences of capital

individuals are closely linked to their attitudes to, and behaviors within, the field. Capital gives form and coherence to the various activities of an individual across the different spheres of life (Wacquant, 2006). Bourdieu (1998) developed a diagram in order to illustrate the relationship between social positions, habitus and the choices made by the social agents in the most diverse domains of practice, e.g. in music or politics, food or sport (Figure 1–4).

FIGURE 1–4

The space of social positions and lifestyles

The position, and the attitudes associated with it, of any individual or group in social space may be charted by two coordinates: (1) the overall volume of capital, (2) the composition of the capital. According to Bourdieu (1998) social space is ‘’a spatial metaphor for how people are related to each other with respect to forms of capital’’. Individuals face a differentiated social space at which the various spheres of life (e.g. science, the economy, the law, politics,

work, religion or art) tend to form distinct fields. The fields are endowed with their own rules, forms of authority and regularities (Wacquant, 2006). Bourdieu (1998) reveals in his work that the space of social positions is organized by two principles of differentiation; economic capital and cultural capital. The vertical division of the diagram classifies individuals holding large volumes of either capital against individuals deprived of both. The horizontal opposition classifies individuals who possess much economic capital but few cultural assets against those who possess much cultural capital but few economic capital. Individuals are located in social space in such a way that the closer they are to each other, the more they have in common in those two dimensions and the more apart they are from each other, the less they have in common (Bourdieu, Sapiro and McHale, 1991). Note that every social space is defined by capital and that there are different forms of capital, however Bourdieu (1998) focuses his work mainly on the relative position of economic capital to cultural capital. Individuals continually try to maintain or improve their position in social space by applying strategies of conversion whereby one type of capital is transmuted into another (Wacquant, 2006).

2000). This may indicate that poorer people give priority to the function of food and choose ‘’what will last’’ and seek ‘’value for money’’ (Øygard, 2000). Besides, Øygard (2000) demonstrated that those individuals which are richest in cultural capital are strongly concerned with healthy and exotic food (i.e. ‘’food as form’’) and less interested in filling food (i.e. ‘’food as function’’). This may reflect that individuals who possess less cultural capital are not very eager to develop a healthy lifestyle and they have a more comfortable attitude towards their bodies than individuals holding large volumes of cultural capital. Bourdieu (1998) also argues that cultural capital is the most important factor regarding health behaviors. Food tastes depend on the attitudes individuals with different forms of capital have about the body. Individuals which are richest in cultural capital are more oriented towards healthy food because of their constant concern with health and appearance and these people tend to treat the body ‘’as a project’’ (Bourdieu, 1998). On the other hand, individuals poor in cultural capital tend to treat the body ‘’as a machine’’ and give priority to the food’s function. With regard to exotic food, it has been observed that individuals who introduce novelties (e.g. exotic food) into the food culture are usually individuals holding large volumes of cultural capital (Øygard, 2000). Finally, in relation to cultural goods, research suggests that to appreciate a symphony or a work of art ‘’presupposes mastery of the specialized symbolic code of which it is a materialization, which in turn requires that the individual possesses the proper kind of cultural capital’’ (Wacquant, 2006: 9). Mastery of this symbolic code can be acquired by osmosis in the individual’s social space or by explicit learning. Hence, the composition of the capital of individuals affects the way in which they value various cultural goods.

2.

C

ONCEPTUAL MODEL

The literature reviewed in the preceding chapter provides a theoretical foundation for analyzing the role of different forms of capital in explaining a MNC’s ability to engage in knowledge transfer on intra-organizational level. The notion of economic, cultural, social and symbolic capital are presented in order to explain differences in attitudes towards learning and knowledge sharing within the organizational field.

Integrating the literature, a conceptual model identifying the key constructs included in the study is provided in Figure 2–1. The conceptual model presents attitudes to learning and knowledge sharing as a consequence of four antecedent factors (i.e. economic capital, cultural capital, social capital and symbolic capital) moderated by the effect of MNCs’ present knowledge transfer practices. Besides, the effect of employees’ attitudes to learning and knowledge sharing on the performance of MNCs is shown. Each of these constructs is now described in detail and research hypotheses are presented.

FIGURE 2–1 Conceptual model

(source: Own design)

2.1 INDIVIDUAL CAPITAL AND ATTITUDES TO LEARNING AND KNOWLEDGE SHARING

Effective knowledge management has to take into consideration the underlying characteristics of the organization’s knowledge base in order to contribute to organizational performance (Li et al., 2010). Knowledge management initiatives will fail if the underlying characteristics of the MNC’s knowledge base are inappropriate. As discussed in the preceding chapter, capital of individuals is closely linked to their attitudes to, and behaviors within, distinct fields. Wacquant (2006) argued that the composition of capital gives form and coherence to the various activities of an individual at work. Hence, effective knowledge management should take into account the composition of capital that individuals draw on in order to pursue their choices with regard to learning and knowledge sharing. Collectively, I argue that the enhancement of individual capital, as the foundation of individuals’ choices with regard to learning and knowledge sharing, is beneficial for the willingness of employees to learn and share their knowledge and expertise. Therefore, I hypothesize the following:

Hypothesis 1: Individual capital has a positive effect on attitudes to learning within

a MNC.

Hypothesis 2: Individual capital has a positive effect on attitudes to knowledge sharing

within a MNC.

2.1.1 Economic capital and attitudes to learning and knowledge sharing

An appropriate reward mechanism maintains and enhances the motivation of employees to learn and share knowledge (Davenport and Prusak, 1998). Cohen (1998: 31) argues that ‘’people’s time and energy are limited and they will choose to do what they believe will give them a worthwhile return on those scarce resources’’. Employees decide whether any reward that is offered fits the value of learning and knowledge sharing. The reward could be in the form of a ‘’hard’’ tangible benefit, such as economic capital (e.g. income or a bonus). Economic capital emerges as an important motivating factor for employees with regard to knowledge management initiatives. Hence, employees holding large volumes of economic capital are more inclined to engage in learning and knowledge sharing. Accordingly, I argue that economic capital is an effective force for inspiring employees’ willingness to learn and share knowledge. Therefore, I hypothesize the following:

Hypothesis 1a: Economic capital has a positive effect on attitudes to learning within

Hypothesis 2a: Economic capital has a positive effect on attitudes to knowledge sharing

within a MNC.

2.1.2 Cultural capital and attitudes to learning and knowledge sharing

The influence of cultures is a key component that has a critical impact on individuals’ development and their conceptions (Tundui, 2012). Knowledge is processed differently by representatives of different national cultures. In MNCs employees have the opportunity to interact with many different colleagues possessing diverse knowledge. This requires that employees are able to communicate their knowledge to and understand the knowledge possessed by such a diverse pool of people (Reinholt, Pedersen and Foss, 2011). However, employees differ in their ability to engage in learning and knowledge sharing. One of the aspects in which employees vary in their ability to learn and share knowledge is the extensiveness of the knowledge they possess (Martin and Salomon, 2003). Cultural capital in the form of officially recognized and guaranteed competences determines the extensiveness of the knowledge individuals possess (Wacquant, 2006). For employees attitudes to learning, this implies that extensiveness of prior knowledge provides a better foundation for absorbing new knowledge, since it enhances the likelihood that the incoming knowledge is related to what employees already know (Cohen and Levinthal, 1990). With regard to employees attitudes to knowledge sharing, extensiveness of prior knowledge implies that employees are better equipped to recognize how their knowledge could be valuable to colleagues. Therefore, the more extensive employees’ existing knowledge is, the greater the chance that learning and knowledge sharing occur on a regular basis. This is further strengthened by arguments in the motivation literature to the effect that feelings of competence are important to maintaining and increasing motivation (Deci and Ryan, 2000; Reinholt et al., 2011). Employees with extensive knowledge (i.e. cultural capital) feel more competent to engage in learning and knowledge sharing and may therefore experience more willingness to learn and share knowledge. Accordingly, I argue that the enhancement of cultural capital, as the foundation for absorbing new knowledge and understanding how knowledge could be valuable to others, is beneficial for the willingness of employees to learn and share their knowledge. Therefore, I hypothesize the following:

Hypothesis 1b: Cultural capital has a positive effect on attitudes to learning within

Hypothesis 2b: Cultural capital has a positive effect on attitudes to knowledge sharing

within a MNC.

2.1.3 Social capital and attitudes to learning and knowledge sharing

Teams, relationships and networks are frequently mentioned as important elements in transferring knowledge effectively (Yang and Chen, 2007). The results of Szulanski’s (1996) study proved that an arduous relationship is a significant impediment to the occurrence of knowledge transfer. Liu (2011) suggested that strong network ties promote the socio-emotional support that generates bonding and trust between individuals. This would increase the sense of goodwill and encourages members to exchange more information and ideas. Besides, Wasko and Faraj (2005) also noted that individuals had greater intention to share their knowledge when they were embedded in a network with strong ties. Each tie in an employee’s network of relationships represents a channel through which knowledge can flow to and from the employee (Reinholt et al., 2011). Moreover, Reinholt et al. (2011) argue that employees holding large volumes of social capital are not only in a position to obtain access to a large amount of knowledge, but are also perceived as attractive knowledge sharing relations by others. Accordingly, I argue that employees who possess much social capital are more inclined to engage in learning and knowledge sharing. Therefore, I hypothesize the following:

Hypothesis 1c: Social capital has a positive effect on attitudes to learning within

a MNC.

Hypothesis 2c: Social capital has a positive effect on attitudes to knowledge sharing

within a MNC.

2.1.4 Symbolic capital and attitudes to learning and knowledge sharing

compliment of being invited to participate in the workshops, and after that being involved in global strategic projects (on the basis of an established reputation), was perceived as immensely rewarding’’. The enhancement of symbolic capital can be perceived as a long-term project. With regard to knowledge management initiatives, symbolic capital emerges as an important motivating factor for employees to demonstrate their altruistic and pro-social behaviors (Hall, 2001). Hence, employees holding large volumes of symbolic capital are more eager to engage in learning and knowledge sharing. Accordingly, I argue that symbolic capital is an effective strength for inspiring employees’ willingness to learn and share knowledge.

Therefore, I hypothesize the following:

Hypothesis 1d: Symbolic capital has a positive effect on attitudes to learning within

a MNC.

Hypothesis 2d: Symbolic capital has a positive effect on attitudes to knowledge sharing

within a MNC.

2.2 THE MODERATING ROLE OF KNOWLEDGE TRANSFER PRACTICES In addition to presenting four antecedent factors to attitudes to learning and knowledge sharing, Figure 2–1 also depicts one factor moderating these hypothesized associations. This moderating factor will be further explained.

Hypothesis 3: A MNC’s present knowledge transfer practices moderate the effect of

(a) economic capital, (b) cultural capital, (c) social capital, and (d) symbolic capital on attitudes to learning within a MNC.

Hypothesis 4: A MNC’s present knowledge transfer practices moderate the effect of

(a) economic capital, (b) cultural capital, (c) social capital, and (d) symbolic capital on attitudes to knowledge sharing within a MNC.

2.3 PERFORMANCE AND ATTITUDES TO LEARNING AND KNOWLEDGE SHARING

The knowledge base of a MNC is considered as an important asset since it has great potential to improve performance (Tsai, 2001). Nonaka and Takeuchi (1995) argue that the capability of an organization to create new knowledge and communicate it throughout the organization may be a preeminent success factor. Similarly, Yang (2010) states that stimulating employees to transfer their talent and experience into organizational assets enables knowledge creation and sustainable competitive advantage, which ultimately can lead to enhanced organizational performance. Tsai (2001) believes that the learning capacity is important for a MNC’s performance. Knowledge and employee expertise can be seen as important sources of value creation. Though, the overall knowledge transfer effectiveness and contribution to the performance of an organization would not be attained unless employees are willing to learn and share their knowledge and expertise. Hence, employees’ willingness to learn and share knowledge contributes to the enhancement of the performance of a MNC. Accordingly, I argue that high willingness of employees to learn and share their knowledge and expertise is related to better organizational performance. Therefore, I hypothesize the following:

Hypothesis 5a: Attitudes to learning have a positive effect on the performance of a MNC. Hypothesis 5b: Attitudes to knowledge sharing have a positive effect on the performance

of a MNC.

3.

R

ESEARCH DESIGN

This chapter elaborates on how the research is designed and in what way the data are collected. The research strategy and method will be explained in detail.

3.1 RESEARCH STRATEGY

The aim of this study is to generate an understanding of the factors affecting individuals’ learning and knowledge sharing behavior within MNCs. Based on existing literature and theories hypotheses are formulated. These hypotheses are tested by observing specific cases in this study. According to Thomas (2004), case studies will generate a rich and complex understanding of the phenomenon. Case study research can be explanatory, descriptive or exploratory (Yin, 1993). This study uses explanatory case study research, which aims for the intensive examination of a single or a small number of units of interest (Thomas, 2004). These units of interest can be industries, organizations, departments or smaller units such as work groups. The case study is used for explanatory purposes in the sense that it is an attempt to understand to role of individual capital (i.e. economic, cultural, social and symbolic capital) in explaining differences in attitudes to learning and knowledge sharing and how it affects organizational performance. Explanatory case studies can be useful for theory-testing, since in this approach you begin with a set of specific hypotheses and then see if these work in real world situations (Thomas, 2004). The main disadvantage of using a case study is that the findings often cannot be generalized. The research strategy will be elaborated on in further depth by looking at the research procedures.

3.2 CASE STUDY

mainly satisfy the demand for accommodation, food and beverage as well as meeting arrangements for tourists, travelers and local residents (Kotler, Bowen and Makens, 2006). Kahle (2002)argues that the service processes in the hospitality industry are knowledge-based or knowledge-intensive due to the great influence and use of ICT. Sheldon (1997) claims that the tourism and hospitality industry is one of the largest users of ICT. Moreover, the hospitality industry is knowledge-intensive as a result of the character of service products, where the service delivery occurs based on interaction between employees and guests and where it is required that employees are knowledgeable of guests’ needs and wishes in order to realize guest satisfaction (Kahle, 2002; Kotler et al., 2006; Hallin and Marnburg, 2008). Therefore, learning and knowledge sharing practices are scrupulously important in their operations.

Efforts in knowledge management practices are predominantly observed within large international hotel chains (e.g. Accor, Hilton, InterContinental Hotels Group), which have to deliver an overall service quality standard in their geographically dispersed hotels (Bouncken, 2002; Baldwin-Evans, 2006). Hence, large international hotel chains acknowledge their position in a knowledge-intensive industry that requires continuous advancement of learning and knowledge sharing practices in order to improve organizational performance (Hallin and Marnburg, 2008).

MKG Hospitality publishes on a yearly basis the ‘’World top 100 hotel groups’’, ranked by the total number of rooms (MKG, 2012). MKG’s ‘’World top 100 hotel groups’’ served as a sample frame for the case study. The case study organization was selected on the basis of size and degree of internationalization since existing literature addresses that knowledge management practices are predominantly observed in large international hotel chains (Bouncken, 2002; Baldwin-Evans, 2006; Hallin and Marnburg, 2008). The international hotel chain selected as case study organization is concerned with knowledge management practices, and acknowledges in their annual report activities in respect to learning and knowledge sharing.